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Data Visualization (Python)
Example 1¶
I have written a sript a while ago to plot a long sequence of data. In this first example I plot data represented LIDAR scanning of a road with segments having either cleanded ditches or not, while registering a lot I am intrested here in representing three quantitative variables extracted from LIDAR pointcloud.
read moreHTML (From 100Days of Web)
Intro¶
Numpy (Cool library)
Numpy Intro¶
No need to say a lot here, NumPy is useful and you need it all over the place. In my favorite book about Data Science Jake says "provides an efficient interface to store and operate on dense data buffers." and then make a survey of many goodies fo numpy library. VanderPlas, Jake. Python Data Science Handbook read more
Clustering
Intro¶
Cluster analysis is the method in data analysis that is used to classify data points. Clustering pick out pattern in unlabeled data and group items in meaningful way. As a programmer you have to write scripts that learns the inherent structure of the data with no labeled examples provided (unsupervised learning). The program under the hood analyzes the data it encounters and tries to identify patterns and group the data on output.
read morePerlin Noise
Perlin Noise Algoritm¶
Ken Perlin is the creator of perlin noise algoritm used in generating textures and terrain-like images to name a few applications of this smooth noise. This arcticle is about application of it and not so much about the algorithms steps.
Perlin in Python¶
In Python in 2023 there is no built-in implementation of the Perlin noise algorithm. Since I can't quickly (time isn't a key factor) refactor this implementation from java to python https://mrl.cs.nyu.edu/~perlin/noise/ read more
Understanding Probability With Python
Probability is a branch of mathematics that is often used to make decisions and is concerned with measuring uncertainty.
Introduction¶
Sets¶
Set data types in Python have rules similar to set in mathematics: collections are unordered, unchangeable (only removal or addition is applicable), store unique items, and are unindexed.
Experiments and Event¶
Experiment return values for observation(s), and observations have some level of uncertainty. Single possible outcome of an experiment is a sample point in a set called sample space. Set sample space stores all possible sample points for one experiment. If your experiment is a set of n sample points the full sample space is written as follows for example of coin flip:
read moreStatistical Distributions (Common ones)
Introduction¶
A probability distribution in statistics is a function that returns the possible values for a variable with different occurence rate (how often values occur). Distribution in nature and society tend to fit pattern with ocasionally occuring exceptions (isn't absence of pattern is a pattern too?).
Probability Mass Function¶
Discrete random variable has probability mass function (PMF) being a particular type of probability distribution read more
Jump In pymc
Install¶
To simply install pymc was not enough on my computer, neither on Google Colab it worked to simply use library after
!pip install. Apparently my laptop hadn't a working fortran of C compiler- the message that I got was:Aesara will be unable to compile C-implementations and will default to Python. Performance may be severely degraded. To remove this warning, set Aesara flags cxx to an empty string.read morelinks